Agricultural Typologies – Gabon

The Hand-in-Hand (HiH) Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty. The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows: • Critical with moderate agricultural opportunities. • Medium priority with moderate agricultural opportunities. • Low priority. • High priority. • Medium priority with high agricultural opportunities. • Low priority with high agricultural opportunities. • High-performance. ** Data Components** The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities. The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services). The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts. For more information please refer to the **Guidance note** listed under Data and Resources section. **Supplemental Information** The Agricultural Typology analysis is a dataset developed in the framework of the HiH, which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.

The Hand-in-Hand (HiH) Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty. The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows: • Critical with moderate agricultural opportunities. • Medium priority with moderate agricultural opportunities. • Low priority. • High priority. • Medium priority with high agricultural opportunities. • Low priority with high agricultural opportunities. • High-performance. **Data Components** The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities. The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services). The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts. For more information please refer to the **Guidance note** listed under Data and Resources section. **Supplemental Information** The Agricultural Typology analysis is a dataset developed in the framework of the HiH, which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.

The Hand-in-Hand Initiative (HiH) agricultural typologies Regional Initiative for the Amazon, was prepared for the Amazon Cooperation Treaty Organization (ACTO), which includes 8 countries: Bolivia, Brazil, Colombia, Ecuador, Peru, Guyana, Suriname, and Venezuela. The HiH Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty. The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows: • Critical with moderate agricultural opportunities. • Medium priority with moderate agricultural opportunities. • Low priority. • High priority. • Medium priority with high agricultural opportunities. • Low priority with high agricultural opportunities. • High-performance. **Data Components** The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities. The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services). The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts. **Supplemental Information** The Agricultural Typology analysis is a dataset developed in the framework of the HiH, which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.

The Hand-in-Hand Initiative (HiH) agricultural typologies Regional Initiative for the Amazon, was prepared for the Amazon Cooperation Treaty Organization (ACTO), which includes 8 countries: Bolivia, Brazil, Colombia, Ecuador, Peru, Guyana, Suriname, and Venezuela. The HiH Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty. The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows: • Critical with moderate agricultural opportunities. • Medium priority with moderate agricultural opportunities. • Low priority. • High priority. • Medium priority with high agricultural opportunities. • Low priority with high agricultural opportunities. • High-performance. **Data Components** The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities. The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services). The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts. **Supplemental Information** The Agricultural Typology analysis is a dataset developed in the framework of the HiH, which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.

The Hand in Hand Initiative (HiH) - Building Resilience in the Dry Corridor and Arid Zones of the Central American Economic Integration System (SICA) regional initiative, is being developed since 2022, involves eight countries: Belize, Costa Rica, El Salvador, Honduras, Guatemala, Nicaragua, Panama and the Dominican Republic. The HiH Agricultural Typology analysis targets the identification of micro-regional level innovation opportunities, bottlenecks, and investment gaps. This concept is based on the production possibilities frontier applied to farm activities. It draws on household-level surveys and geospatial data on agroecological conditions, accessibility, and poverty. The final Agricultural Typology consists of a classification representing a combination of agricultural potential, agricultural efficiency, and priority (poverty) components in each region. The 7 classes are as follows: • Critical with moderate agricultural opportunities. • Medium priority with moderate agricultural opportunities. • Low priority. • High priority. • Medium priority with high agricultural opportunities. • Low priority with high agricultural opportunities. • High-performance. **Data Components** The Agricultural Potential component provides the maximum agricultural income smallholder farmers can attain if performing at maximum capacity (their own, as well as of the markets, productive infrastructure, and basic services surrounding them). It is determined by both the biophysical and economic factors. The interaction of these two sets of elements establishes the maximum income a farmer can earn from agricultural activities. The Agricultural Efficiency component defines how much of the potential is attained by farmers in a region under current conditions. To increase their efficiency, farmers need to reduce transaction costs in agricultural production and marketing through improved infrastructure (such as roads) and services (such as market information), overcome market failures (access to credit, insurance, land markets, etc.), and receive better access to basic services (such as education and extension services). The Priority component reveals a region’s degree of urgency for investments in development, measured in terms of the wellbeing of the local population, the target beneficiaries of agricultural innovation efforts. **Supplemental Information** The Agricultural Typology analysis is a dataset developed in the framework of the HiH, which is an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) aiming to accelerate the agricultural transformation and sustainable rural development to eradicate poverty, and end hunger and all forms of malnutrition.

The raster dataset consists of a 500 m score grid for the crop storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse locations: • Supply: Fruits. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + (“Major Cities Accessibility” * 0.1) + (”Poverty” * 0.1) + ("Human Population Density" * 0.2) + (“Regional Cities Accessibility” * 0.1) +(“Port Accessibility” * 0.1). **Data publication:** 2022-04-11 **Contact points:** Resource Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Dariia Nesterenko](mailto:dariia.nesterenko@fao.org) **Data lineage:** lineage statement Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. 3. OpenStreetMap. 4. Poverty – Atlas AI 2020. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Zipped TIF raster file for Crop Storage Location Score: Fruits (Gabon - ~ 500 m)